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Forecasting with Bayesian multivariate vintage-based VARs

Carriero, A., Clements, M. P. ORCID: https://orcid.org/0000-0001-6329-1341 and Galvao, A. B. (2015) Forecasting with Bayesian multivariate vintage-based VARs. International Journal of Forecasting, 31 (3). pp. 757-768. ISSN 0169-2070

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To link to this item DOI: 10.1016/j.ijforecast.2014.05.007

Abstract/Summary

We consider the forecasting of macroeconomic variables that are subject to revisions, using Bayesian vintage-based vector autoregressions. The prior incorporates the belief that, after the first few data releases, subsequent ones are likely to consist of revisions that are largely unpredictable. The Bayesian approach allows the joint modelling of the data revisions of more than one variable, while keeping the concomitant increase in parameter estimation uncertainty manageable. Our model provides markedly more accurate forecasts of post-revision values of inflation than do other models in the literature.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > ICMA Centre
ID Code:37612
Publisher:Elsevier

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